Hey there,
If you’ve ever shipped an “AI agent” that looked great in a demo… then fell apart in production, you’re not alone.
Most reliability problems don’t come from the model. They come from missing structure.
Here are two agentic design patterns that separate pro-grade builds from beginner setups:
1) Prompt Chaining (assembly line + validation) Take one complex task and split it into 3–5 steps. Each step checks the output of the previous step before moving forward. This gives you natural QA gates, clearer debugging, and fewer silent failures.
Where it shines: document workflows, data cleanup/ETL, reporting, content pipelines. Where it breaks: when you carry too much context forward (token bloat) or let one early mistake cascade.
2) Routing (smart triage to specialists) Instead of one generalist agent, analyze the request and send it to the correct specialist agent/tool. If confidence is low, ask clarifying questions or quarantine edge cases.
Where it shines: customer service, multi-department ops, any workflow with distinct tool paths.
If you want your automations to feel “enterprise-grade,” start with these two patterns before adding more tools.
"More context isn’t always better; context bloat can create hallucinations."
Want a simple checklist to implement chaining + routing in your workflows? Hit reply with “PATTERNS” and I’ll send it.
Best,
AK
